{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Graph_Serctral_Clustering.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "ExQoYP2IJqif",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "d6dbdfda-a601-4b20-c562-818b766b9051"
      },
      "source": [
        "#coding=utf-8\n",
        " \n",
        "#MSC means Multiple Spectral Clustering\n",
        " \n",
        "import numpy as np\n",
        " \n",
        "import scipy as sp\n",
        " \n",
        "import scipy.linalg as linalg\n",
        " \n",
        "import networkx as nx\n",
        " \n",
        "import matplotlib.pyplot as plt\n",
        " \n",
        " \n",
        " \n",
        "def getNormLaplacian(W):\n",
        " \n",
        "    \"\"\"input matrix W=(w_ij)\n",
        "     \n",
        "    \"compute D=diag(d1,...dn)\n",
        "     \n",
        "    \"and L=D-W\n",
        "     \n",
        "    \"and Lbar=D^(-1/2)LD^(-1/2)\n",
        "     \n",
        "    \"return Lbar\n",
        "     \n",
        "    \"\"\"\n",
        "     \n",
        "    #d=[np.sum(row) for row in W]\n",
        "    print(np.array(np.sum(W, axis = 0)))\n",
        "    d = np.array(np.sum(W, axis = 0))[0] \n",
        "    D=np.diag(d)\n",
        "     \n",
        "    L=D-W\n",
        "    \n",
        "    Dn = np.linalg.inv(D)\n",
        "    Dn = Dn**0.5\n",
        "    \n",
        "    #Dn2=np.power(np.linalg.matrix_power(D,-1),0.5)\n",
        "\n",
        "\n",
        "    Lbar=np.dot(np.dot(Dn,L),Dn)\n",
        "     \n",
        "    return Lbar\n",
        " \n",
        " \n",
        " \n",
        "def getKSmallestEigVec(Lbar,k):\n",
        " \n",
        "    \"\"\"input\n",
        "     \n",
        "    \"matrix Lbar and k\n",
        "     \n",
        "    \"return\n",
        "     \n",
        "    \"k smallest eigen values and their corresponding eigen vectors\n",
        "     \n",
        "    \"\"\"\n",
        "     \n",
        "    eigval,eigvec=linalg.eig(Lbar)\n",
        "     \n",
        "    dim=len(eigval)\n",
        "     \n",
        "     \n",
        "     \n",
        "    #查找前k小的eigval\n",
        "     \n",
        "    dictEigval=dict(zip(eigval,range(0,dim)))\n",
        "     \n",
        "    kEig=np.sort(eigval)[0:k]\n",
        "     \n",
        "    ix=[dictEigval[k] for k in kEig]\n",
        "     \n",
        "    return eigval[ix],eigvec[:,ix]\n",
        " \n",
        " \n",
        " \n",
        "def checkResult(Lbar,eigvec,eigval,k):\n",
        " \n",
        "    \"\"\"\n",
        "     \n",
        "    \"input\n",
        "     \n",
        "    \"matrix Lbar and k eig values and k eig vectors\n",
        "     \n",
        "    \"print norm(Lbar*eigvec[:,i]-lamda[i]*eigvec[:,i])\n",
        "     \n",
        "    \"\"\"\n",
        "     \n",
        "    check=[np.dot(Lbar,eigvec[:,i])-eigval[i]*eigvec[:,i] for i in range(0,k)]\n",
        "     \n",
        "    length=[np.linalg.norm(e) for e in check]/np.spacing(1)\n",
        "     \n",
        "    print(\"Lbar*v-lamda*v are %s*%s\" % (length,np.spacing(1)))\n",
        " \n",
        " \n",
        " \n",
        "g=nx.karate_club_graph()\n",
        " \n",
        "nodeNum=len(g.nodes())\n",
        " \n",
        "m=nx.to_numpy_matrix(g)\n",
        "# m is adj matrix\n",
        "#print(m.shape)\n",
        "Lbar=getNormLaplacian(m)\n",
        "# get NormLaplacian\n",
        "k=2\n",
        " \n",
        "kEigVal,kEigVec=getKSmallestEigVec(Lbar,k)\n",
        " \n",
        "print(\"k eig val are %s\" % kEigVal)\n",
        " \n",
        "print(\"k eig vec are %s\" % kEigVec)\n",
        " \n",
        "checkResult(Lbar,kEigVec,kEigVal,k)\n",
        " \n",
        " \n",
        " \n",
        "#did not use k means，just use a simple evidence to judge\n",
        " \n",
        " \n",
        " \n",
        "clusterA=[i for i in range(0,nodeNum) if kEigVec[i,1]>0]\n",
        " \n",
        "clusterB=[i for i in range(0,nodeNum) if kEigVec[i,1]<0]\n",
        " \n",
        " \n",
        " \n",
        "#draw graph\n",
        " \n",
        "colList=dict.fromkeys(g.nodes())\n",
        " \n",
        "for node,score in colList.items():\n",
        " \n",
        "    if node in clusterA:\n",
        "     \n",
        "        colList[node]=0\n",
        " \n",
        "    else:\n",
        "     \n",
        "        colList[node]=1\n",
        "#print(colList[1])\n",
        "#colList[1] = 2\n",
        "\n",
        "plt.figure(figsize=(8,8))\n",
        " \n",
        "pos=nx.spring_layout(g)\n",
        " \n",
        "nx.draw_networkx_edges(g,pos,alpha=0.4)\n",
        " \n",
        "nx.draw_networkx_nodes(g,pos,nodelist=colList.keys(),\n",
        "node_color=list(colList.values()),\n",
        "cmap=plt.cm.Reds_r)\n",
        " \n",
        "nx.draw_networkx_labels(g,pos,font_size=10,font_family='sans-serif')\n",
        " \n",
        "plt.axis('off')\n",
        " \n",
        "plt.title(\"karate_club spectral clustering\")\n",
        " \n",
        "plt.savefig(\"spectral_clustering_result.png\")\n",
        " \n",
        "plt.show()"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[16.  9. 10.  6.  3.  4.  4.  4.  5.  2.  3.  1.  2.  5.  2.  2.  2.  2.\n",
            "   2.  3.  2.  2.  2.  5.  3.  3.  2.  4.  3.  4.  4.  6. 12. 17.]]\n",
            "k eig val are [2.77555756e-17+0.j 1.32272329e-01+0.j]\n",
            "k eig vec are [[-0.32025631 -0.2963998 ]\n",
            " [-0.24019223 -0.11341389]\n",
            " [-0.25318484  0.00897113]\n",
            " [-0.19611614 -0.11512758]\n",
            " [-0.13867505 -0.2671717 ]\n",
            " [-0.16012815 -0.34638736]\n",
            " [-0.16012815 -0.34638736]\n",
            " [-0.16012815 -0.08992931]\n",
            " [-0.17902872  0.05282964]\n",
            " [-0.1132277   0.05563406]\n",
            " [-0.13867505 -0.2671717 ]\n",
            " [-0.08006408 -0.0853954 ]\n",
            " [-0.1132277  -0.09868424]\n",
            " [-0.17902872 -0.04671125]\n",
            " [-0.1132277   0.11251508]\n",
            " [-0.1132277   0.11251508]\n",
            " [-0.1132277  -0.28226926]\n",
            " [-0.1132277  -0.09119046]\n",
            " [-0.1132277   0.11251508]\n",
            " [-0.13867505 -0.03091925]\n",
            " [-0.1132277   0.11251508]\n",
            " [-0.1132277  -0.09119046]\n",
            " [-0.1132277   0.11251508]\n",
            " [-0.17902872  0.19602288]\n",
            " [-0.13867505  0.13544115]\n",
            " [-0.13867505  0.14515535]\n",
            " [-0.1132277   0.12748466]\n",
            " [-0.16012815  0.1349113 ]\n",
            " [-0.13867505  0.08022324]\n",
            " [-0.16012815  0.18201707]\n",
            " [-0.16012815  0.07139028]\n",
            " [-0.19611614  0.12810813]\n",
            " [-0.2773501   0.25162746]\n",
            " [-0.33011265  0.26979354]]\n",
            "Lbar*v-lamda*v are [5.87070581 3.87824347]*2.220446049250313e-16\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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6KWDPLMXVc63HhK5s2Z6SfmAAO5aEePB+wBMlHOYqwvtpR7ktVHO6iUYWYl7n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\nLGAaY4wxGfj/JsQAh42BtOEAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}